Service providers (e.g., wireless and cellular services) and device manufacturers are continually challenged to deliver value and convenience to consumers by, for example, providing compelling network services and advancing the underlying technologies. One area of interest has been the development of services and technologies for characterizing user behavior with respect to the user's interactions with a device (e.g., a cell phone, smartphone, or other mobile device). More specifically, characterizing user behavior relies, for instance, on correlating user interactions with the device (e.g., user engaging various functions and features of the device to place a phone call, invoke an application, play a media file, snap a picture, etc.) with a given context associated with the user or device (e.g., a location, time, date, activity, etc.). However, service providers and device manufacturers face significant technical challenges in making such a correlation because of the difficulties of characterizing more complex user contexts. As a result, the ability to automate certain user interactions with the mobile device in the instance of a given context is limited. For example, if a user desires to have their mobile device automatically log mileage and route data amassed as they jog via usage of a software application, the mobile device must be properly trained to detect and perceive context information (e.g., mileage and route data) pertaining to this type of software interaction (e.g., mileage logging) in correlation with the correct moment/context (at the onset of or during the time of jogging).